class_docstr: Pointwise exponential of a positive semi-definite kernel.
  
  Produces `exp(k(x, y))`, where `k(., .)` is the input positive semi-definite
  kernel.
  
  #### References
  [1]: John Shawe-Taylor and Nello Cristianini. Kernel Methods for Pattern
  Analysis. Section 3.2. 2004.
  https://people.eecs.berkeley.edu/~jordan/kernels/0521813972c03_p47-84.pdf
code: def _matrix(self, x1, x2):
      kernel_matrix = self._kernel.matrix(x1, x2)
      return tf.exp(kernel_matrix)
  
file_path: probability/tensorflow_probability/python/math/psd_kernels/pointwise_exponential.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.math.psd_kernels import positive_semidefinite_kernel
label_desc: Use image node_id 4 for calling the PointwiseExponential obj's underlying member method code with example usage: obj._matrix(x1, x2) and returns: tf